Month: February 2017

In the information sciences the definitions below are the very foundation of informatics: p. 13

Data consists of facts. Facts are observations or measurements about the world. For example, ‘today is Tuesday’

Knowledge defines relationships between data. The rule ‘tobacco smoking causes lung cancer’ is an example of knowledge. Such knowledge is created by identifying recurring patterns in data, for example across many different patients. We learn that events usually occur in a certain sequence, or that an action typically has a specific effect. Through the process of model abstraction, these observations are then codified into general rules about how the world works.

As well as learning such generalized ‘truths’ about the world, once can also learn knowledge that is specific to a particular circumstance. For example, we can create patient specific knowledge by observing a patient’s state over time. By abstracting away patterns in what is observed, one can arrive at specific knowledge such as ‘following treatment with anti-hypertensive medication, there has been no decrease in patient’s blood pressure over the last 2 months.

Information is obtained by the application of knowledge to data. Thus, the datum that ‘the patient’s blood pressure is 125/70 mmHg’ yields information if it tells us something new. In the context of managing a patient’s high blood pressure, using our general knowledge of medicine, and patient specific knowledge, the datum may allow us to draw the inference that the patient’s blood pressure is now under control.

How variations in the structure of clinical messages affect the way in which they are interpreted: p.36-43

What a message is meant to say when it is created, and what the receiver of a message understands, may not be the same. This is because what we humans understand is profoundly shaped by the way data are presented to us, and by the way we react to different data presentations. Thus it is probably as important to structure data in a way so that they can be best understood, as it is to ensure that the data are correct in the first place. What a clinician understands after seeing the data in a patient record and what the data actually show are very different things.

When sending a message, we have to make assumptions about the knowledge that the receiver has, and use that to shape our message. There is no point in explaining what is already known, but is equally important not to miss out important details that the receiver should know to draw the right conclusions. The knowledge share between individuals is sometimes called common ground.

The structure of a message determines how it will be understood. The way clinical data are structured can alter the conclusions a clinician will draw from data.

The message that is sent may not be the message that is received. The effectiveness of communication between two agents is dependent upon:

the communication channel which will vary in capacity to carry data and noise which distorts the message

the knowledge possessed by the agents, and the common ground between them

the resource limitations of agents including cognitive limits on memory and attention

the context within which the agents find themselves which dictate which resources are available and the competing tasks at hand.

Grice’s conversational maxims provide a set of rules for conducting message examples:

maximum of quantity: say on what is needed.

maximum of quality: make you contribution one that is true.

maximum of relevance: say only what is pertinent to the context of the conversation at the moment.

maximum of manner: avoid obscurity of expression, ambiguity, be brief and orderly.

Medical record’s basic functions: p.112

provides means of communicating between staff who are actively managing a patient.

during the period of active management of a patient’s illness, the record strives to be the single data access point for workers managing a patient. All test results, observations and so forth should be accessible through it.

the record offers and informal ‘working space’ to record ideas and impressions that help build up a consensus view, over the period of care, of what is going on with the patient.

once an episode of care has been completed, the record ultimately forms the single point at which all clinical data are archived, for long-term use.

The traditional way the EMR – record used in care is to be a passive supporter of clinical activity. An active EMR may suggest what patient information needs to be collected, or it might assemble clinical data in a way that assists a clinician in the visualization of a patient’s clinical condition. p.119

There are two quite separate aspects to record systems:

the physical nature of the way individuals interact with it

the way information is structured when entered into or retrieved from the system.

A summative evaluation can be made in three broad categories:

a user’s satisfaction with the service

clinical outcome changes resulting from using the service

any economic benefit of the service

Technology can be applied to a problem in a technology-drive or a problem-driven manner. Information systems should be created in a problem-driven way, starting with an understanding of user information problems. Only then is it appropriate to identify if an how technology should be used.

Providing access methods that are optimized to local needs can enlarge the range of clinical context s in which evidence is used. p.177

p.354:

AI systems are limited by the data they have access to, and the quality of the knowledge captured withing their knowledge base.

An expert system is a program that captures elements of human expertise and performs reasoning tasks that normally rely on specialist knowledge. Expert systems perform best in straightforward tasks, which have a predefined and relatively narrow scope, and perform poorly on ill-defined tasks that rely on general or common sense knowledge.

An expert system consists of:

a knowledge base, which contains the rules necessary for the completion of its task

a working memory in which data and conclusions can be stored

an inference engine, which matches rules to data to derive its conclusions.

E-prescribing has been purported to benefit the pharmacy profession in many ways (eg, improved patient medication safety, increased satisfaction with the pharmacy and reduced wait times at the pharmacy).

Respondents also indicated the inability to prescribe controlled substances electronically as problematic. Although the Drug Enforcement Agency (DEA) legalized e-prescribing of controlled substances in June 2010 (after this study was conducted), not all pharmacies or vendors meet the DEA’s requirements to accept or transmit electronic prescriptions from prescribers, and some state boards of pharmacy may place restrictions on controlled substance e-prescribing. Ongoing development of compliant software by pharmacy chains and vendors is vital for facilitating e-prescribing of controlled substances.

A recent study reported no statistically significant differences between the number of unclaimed prescriptions among patients who received standard written prescriptions and patients whose prescriptions were submitted electronically. Patient-reported reasons for not claiming e-prescriptions include perceiving their prescription as unnecessary or not needing their prescription, medication affordability, lack of time, not realizing the medication is at the pharmacy, and no physical evidence of an e-prescription. Prescription fill status notifications are mandated for e-prescribing systems and may help to minimize unclaimed prescriptions if used and acted on by prescribers. However, the fill status notifications still do not guarantee that patients picked up their filled prescriptions.

There have been anecdotal reports from patients that the e-prescription was not at the pharmacy when picking up their prescription.

One of the most salient benefits of e-prescribing is the reduction of preventable medication errors by generating a legible prescription checked by e-prescribing software for drug-drug and other interactions; however, e-prescribing does not completely eliminate preventable medication errors. Data entry errors, such as selecting the wrong drug, may occur from a drop-down menu. Although software vendors continually make efforts to prevent such errors, pharmacists should remain vigilant in detecting such errors occurring because of the e-prescribing software, and research should continually focus on medication error rates from the system as e-prescribing becomes more prevalent. Policy initiatives such as requiring diagnosis codes on electronic, if not all prescriptions, may help reduce data entry and subsequent dispensing errors and improve patient safety.

The effect of e-prescribing on patient safety and
quality of patient care in hospital settings:

Generally, the research findings on the effect of e-prescribing on medication errors were partially attributed to their settings, the system design features, or the nature of prescribers’ work. Studies conducted on homegrown systems (vs. commercial products/systems) or on systems with manual chart review show a higher ability to detect medication errors with e-prescribing. One study stated that design features of e-prescribing such as poor drop-down menu, poor screen design, or inaccurate or incomplete patient medication lists especially in certain diseases can pose a threat to patient safety. Another study that examined the relationship between prescribing errors, use of e- prescribing technology, complexity of tasks and interruptions in healthcare settings reported that common errors that occurred include: selection of incorrect medication, dose, route, and formulation. When prescribers were interrupted when performing tasks on e-prescribing systems, they required almost three times longer to complete complex tasks when compared to simple tasks. Interruptions when using e-prescribing systems were suggested to be a possible contributing factor to medications errors when using this technology possibly due to loss of concentration by the user.

On the receiving end: community pharmacies

Patient safety is commonly thought of in health-
care settings as the freedom from medication errors and patient harm.

Studies on safety of e-prescribing in community
pharmacies are particularly important as they are the recipients of the product (e-prescriptions) of e-prescribing systems. The literature on the safety issues related to e-prescribing use in community pharmacies is sparse when compared to studies that have been conducted in hospital settings. Unlike hospital settings, community pharmacies do not have access to real-time patient information that may help them detect when incorrect information is present on the e-prescription.

Pharmacists need to understand the new kinds of prescribing errors generated using new technologies used in healthcare delivery, especially related to e-prescribing technol- ogy use, for them to be better equipped to detect and prevent errors.

Issues associated with e-prescriptions in pharmacies have been reported to be caused by omission of vital information by prescribers, poor design in pharmacies and physician office and other inherent technology limitations. E- prescribing, like other types of HIT, has the potential to improve patient safety in pharmacies but if poorly designed or implemented can pose a risk to patient safety. Issues arising from using such HIT safely are increasingly being recognized as more healthcare organizations across the health system implement these technologies.

Using HFE to improve safety in technology use in pharmacy

Human Factors Engineering(HFE) is a science focused on studying the interactions between people, work systems, environment and how all these important elements might affect safety and human performance.

Pharmacies can also proactively reduce safety
risks related to using e-prescribing technology. This can be achieved by using HFE methods to identify underlying causes of e-prescribing errors and improve shared situational awareness about issues related to using e-prescribing technology.

HFE approaches are currently being applied to
evaluate the benefits and challenges with HIT in hospital settings but have not been widely used in pharmacies or ambulatory care. Patient safety experts are increasingly obtaining guidance from HFE on how to improve usability of e-prescribing design in hospital settings but no research has looked into community pharmacy. It is clear that usability testing of any HIT is a necessity. A fundamental design principle of technology usability is transparency and visibility. Qualitative studies of use of computerized provider order entry systems in hospital settings applying HFE approaches have uncovered challenges with usability involving physicians and nurses which lead to errors. Application of HFE concepts and techniques to improve e-prescribing safety will require collaborative effort from e-prescribing vendors, prescribers, and pharmacists.

Based on: The majority of the included studies were conducted in North America (almost 64% in the United States and 4% in Canada), 16% addressed e-prescribing systems in European centuries, 9% in the Asian context, and the remaining 7% discussed e-prescribing issues in Australia.

Should we have an inclusion criteria like the studies should be conducted in UK and if there is any other country with similar to NHS system?

Handwritten prescriptions have been associated with certain problems such as the risk of misinterpretation and falsification of handwritten prescriptions and the difficulties of legibility, which prompted the use of electronic prescriptions (e-prescriptions). e-Prescription systems are considered as an instrument to minimize medication errors in pharmacies. Electronically produced prescriptions are transmitted to pharmacists by the physicians over a safe network.

Previous research has shown that health professionals play a vital role in adoption and assessment of HIS . Medication errors are frequent in prescriptions, which are one of the most important outputs in health sector. 20% of medical negligence treatment claims result from medications errors. Prescription errors bring extra costs for individuals and have financial impacts on the government. These errors can occur in various stages such as prescription, transcription, dispensing and drug administration and the effects of these errors have varying levels of severity. In parallel to the developments in technology, e-prescription, which has been developed to prevent errors, involves direct transmission of prescriptions from the working environment of physicians to pharmacies via computers. e-Prescription systems record all format information of a prescription in electronic environment. Health institutions, pharmacy, refunding institution and other individuals/stakeholders can access prescription data to the extent they are authorized to, and thus all operations regarding the supply, refund, register and follow-up of medications can be performed in electronic environment. In other countries such as the United Kingdom, e- prescription can be made in two methods: 1) a mechanism in which prescribers can download a prescription automatically from a central network or a mechanism in which the prescribers can produce an e-prescription. However, the system uses paper in prescription infrastructure. 2) A mechanism in which the prescribers can produce an electronically coded signature and can electronically transmit the prescription to the pharmacy rather than physical transport made by the patient. Although verbal prescriptions or those sent by facsimile are legal in the United States, only electronic or handwritten prescriptions are valid in countries like United Kingdom and Holland. Pharmacists can save time by processing the prescriptions which they do not have to manually enter pharmacy information system.

‘Electronic prescription’. ‘e-prescription’ or ‘e-prescribing’
is a computer based application which utilizes the internet to create, broadcast and fill out a medical prescription form. It has taken the place of paper based prescription or fax based prescriptions.

The purpose of this latest technology in the medical field is
to provide patients with an efficient, safe and time saving mode of administering prescriptions. This technology directly transmits the prescription to the pharmacist ensuring there are no errors in understanding the prescribed drug. The use of e? prescription also ensures better health care for the patients as it helps the doctors in many ways to diagnose and prescribe the patient more effectively. This technology has many options that help doctors like the option of providing complete prescription history and other medical conditions of the patients at a click and giving warnings and alerts to the doctor in cases of prescriptions that the system checks are against the medical history of the patient.

It ensures that precious time is saved of the physicians
clarifying their drugs to the pharmacists resulting in more time for the doctor to serve his patient. The purpose of E? Prescription is not just to help the patient but to help everyone associated with the medical industry: the option of automated refill request ensures that hospitals do not lack any necessary medications and their refill process is completed before time. The purpose of this technology is also to serve societal issues and in cases of drug recalls this technology has an option of maintaining the records of patient who were prescribed a particular medicine and by just a click all those patients with that prescribed medicine can be contacted easily and informed about the drug fall out. The use of this technology is not limited to patients and doctors only, it also serves the insurance and other regulatory bodies in assessing records of patients much quicker than the manual systems. In short, the purpose of this innovation is to serve many aspects of patient health care and other related issues at the same time.

Patient Safety

Patient security is important for the healthcare industry.
Adverse drug effects happen across the world on a daily basis, which is why health is an important part of a community’s budget.
E-prescription avoids errors which used to appear with
paper based prescriptions: e.g. a wrong drug or an out of stock drug, a wrong quantity of dosage, repeating medicines, exclusion of information or badly written prescriptions. Such problems mean the pharmacist must call up the medical authorities to confirm the prescription details. This delays the process of providing proper healthcare at the proper time to the patients. They increase expenses as well as time spent on correcting mistakes. Not all mistakes are noted, which may result in harm or even death. Most e-prescription applications have a built in ‘point of care decision’ which detects many errors in the prescription before sending it out. It asks the user to confirm about allergies, verify dosage precision and point
out out the possible reactions between the prescribed drugs before the e-prescription is sent out.